Data-Driven Discovery of Stochastic Differential Equations

Data-Driven Discovery of Stochastic Differential Equations

Stochastic differential equations (SDEs) are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different sources. The identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data a...

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Bibliographic Details
Main Authors: Yasen Wang, Huazhen Fang, Junyang Jin, Guijun Ma, Xin He, Xing Dai, Zuogong Yue, Cheng Cheng, Hai-Tao Zhang, Donglin Pu, Dongrui Wu, Ye Yuan, Jorge Gonçalves, Jürgen Kurths, Han Ding
Format: Article
Language:English
Published: Elsevier 2022-10-01
Series:Engineering
Subjects:
Data-driven method
System identification
Sparse Bayesian learning
Stochastic differential equations
Random phenomena
Online Access:http://www.sciencedirect.com/science/article/pii/S209580992200145X

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